Anticipating the effects of visual gravity during simulated self-motion: estimates of time-to-passage along vertical and horizontal paths

By simulating self-motion on a virtual rollercoaster, we investigated whether acceleration cued by the optic flow affected the estimate of time-to-passage (TTP) to a target. In particular, we studied the role of a visual acceleration (1 g = 9.8 m/s(2)) simulating the effects of gravity in the scene, by manipulating motion law (accelerated or decelerated at 1 g, constant speed) and motion orientation (vertical, horizontal). Thus, 1-g-accelerated motion in the downward direction or decelerated motion in the upward direction was congruent with the effects of visual gravity. We found that acceleration (positive or negative) is taken into account but is overestimated in module in the calculation of TTP, independently of orientation. In addition, participants signaled TTP earlier when the rollercoaster accelerated downward at 1 g (as during free fall), with respect to when the same acceleration occurred along the horizontal orientation. This time shift indicates an influence of the orientation relative to visual gravity on response timing that could be attributed to the anticipation of the effects of visual gravity on self-motion along the vertical, but not the horizontal orientation. Finally, precision in TTP estimates was higher during vertical fall than when traveling at constant speed along the vertical orientation, consistent with a higher noise in TTP estimates when the motion violates gravity constraints

Processing of targets in smooth or apparent motion along the vertical in the human brain: an fMRI study

Neural substrates for processing constant speed visual motion have been extensively studied. Less is known about the brain activity patterns when the target speed changes continuously, for instance under the influence of gravity. Using functional MRI (fMRI), here we compared brain responses to accelerating/decelerating targets with the responses to constant speed targets. The target could move along the vertical under gravity (1g), under reversed gravity (-1g), or at constant speed (0g). In the first experiment, subjects observed targets moving in smooth motion and responded to a GO signal delivered at a random time after target arrival. As expected, we found that the timing of the motor responses did not depend significantly on the specific motion law. Therefore brain activity in the contrast between different motion laws was not related to motor timing responses. Average BOLD signals were significantly greater for 1g targets than either 0g or -1g targets in a distributed network including bilateral insulae, left lingual gyrus, and brain stem. Moreover, in these regions, the mean activity decreased monotonically from 1g to 0g and to -1g. In the second experiment, subjects intercepted 1g, 0g, and -1g targets either in smooth motion (RM) or in long-range apparent motion (LAM). We found that the sites in the right insula and left lingual gyrus, which were selectively engaged by 1g targets in the first experiment, were also significantly more active during 1g trials than during -1g trials both in RM and LAM. The activity in 0g trials was again intermediate between that in 1g trials and that in -1g trials. Therefore in these regions the global activity modulation with the law of vertical motion appears to hold for both RM and LAM. Instead, a region in the inferior parietal lobule showed a preference for visual gravitational motion only in LAM but not RM

Representation of visual gravitational motion in the human vestibular cortex

How do we perceive the visual motion of objects that are accelerated by gravity? We propose that, because vision is poorly sensitive to accelerations, an internal model that calculates the effects of gravity is derived from graviceptive information, is stored in the vestibular cortex, and is activated by visual motion that appears to be coherent with natural gravity. The acceleration of visual targets was manipulated while brain activity was measured using functional magnetic resonance imaging. In agreement with the internal model hypothesis, we found that the vestibular network was selectively engaged when acceleration was consistent with natural gravity. These findings demonstrate that predictive mechanisms of physical laws of motion are represented in the human brain

In situ sulphated CuOx/ZrO2 and CuOx/sulphated-ZrO2 as catalysts for the reduction of NOx with NH3 in the presence of excess O2

Sulphated catalysts containing the same amount of sulphates (2.6 SO4 nm2) and a different amount of copper (0.3–3.9 Cu atoms nm2), Cu/SZ, were prepared by impregnation of sulphated-ZrO2 with toluene solutions of Cu(acetylacetonate)2. Sulphated catalysts containing the same amount of copper (0.3 or 2.5 atoms nm2) and a different amount of sulphates (up to 4.9 SO2 nm2), Cu/ZSg, were prepared by sulphation of CuOx/ZrO2 (Cu/Z) via the gas-phase. Samples were characterised by Fourier transformed IR spectroscopy. The selective catalytic reduction of NO with NH3 in the presence of excess O2 (SCR reaction), the NH3 + O2 and the NO + O2 reactions were studied in a flow apparatus. Activity and selectivity did not depend on the sulphation method used for catalyst preparation but depended on the amount of copper and sulphate, particularly on the sulphate/copper ratio. As on Cu/Z, on Cu/SZ CuII was active for both SCR and NH3 + O2 reactions. The presence of covalent sulphates caused lower reducibility of CuII to CuI and higher Lewis acid strength of CuI in Cu/SZ than in Cu/Z. For (i) SCR, (ii) NH3 + O2 and (iii) NO + O2, Cu/ZSg were less active than the parent Cu/Z. As the sulphate content in Cu/ZSg increased, the NO yield in the NH3 + O2 reaction markedly decreased, thus accounting for the increased selectivity in the SCR reaction. In CuOx/ sulphated-ZrO2 copper ions were less prone reversibly to undergo the redox process CuII/CuI. These findings provide new information on the role of copper and sulphate in determining the activity and selectivity for the SCR with NH

Mal de Debarquement Syndrome: A Matter of Loops?

Introduction: Mal de Debarquement Syndrome (MdDS) is a poorly understood neurological disorder affecting mostly perimenopausal women. MdDS has been hypothesized to be a maladaptation of the vestibulo-ocular reflex, a neuroplasticity disorder, and a consequence of neurochemical imbalances and hormonal changes. Our hypothesis considers elements from these theories, but presents a novel approach based on the analysis of functional loops, according to Systems and Control Theory. Hypothesis: MdDS is characterized by a persistent sensation of self-motion, usually occurring after sea travels. We assume the existence of a neuronal mechanism acting as an oscillator, i.e., an adaptive internal model, that may be able to cancel a sinusoidal disturbance of posture experienced aboard, due to wave motion. Thereafter, we identify this mechanism as a multi-loop neural network that spans between vestibular nuclei and the flocculonodular lobe of the cerebellum. We demonstrate that this loop system has a tendency to oscillate, which increases with increasing strength of neuronal connections. Therefore, we hypothesize that synaptic plasticity, specifically long-term potentiation, may play a role in making these oscillations poorly damped. Finally, we assume that the neuromodulator Calcitonin Gene-Related Peptide, which is modulated in perimenopausal women, exacerbates this process thus rendering the transition irreversible and consequently leading to MdDS. Conclusion and Validation: The concept of an oscillator that becomes noxiously permanent can be used as a model for MdDS, given a high correlation between patients with MdDS and sea travels involving undulating passive motion, and an alleviation of symptoms when patients are re-exposed to similar passive motion. The mechanism could be further investigated utilizing posturography tests to evaluate if subjective perception of motion matches with objective postural instability. Neurochemical imbalances that would render individuals more susceptible to developing MdDS could be investigated through hormonal profile screening. Alterations in the connections between vestibular nuclei and cerebellum, notably GABAergic fibers, could be explored by neuroimaging techniques as well as transcranial magnetic stimulation. If our hypothesis were tested and verified, optimal targets for MdDS treatment could be found within both the neural networks and biochemical factors that are deemed to play a fundamental role in loop functioning and synaptic plasticity

Personalized Treatment Planning Automation in Prostate Cancer Radiation Oncology: A Comprehensive Dosimetric Study

Background: In radiation oncology, automation of treatment planning has reported the potential to improve plan quality and increase planning efficiency. We performed a comprehensive dosimetric evaluation of the new Personalized algorithm implemented in Pinnacle3 for full planning automation of VMAT prostate cancer treatments. Material and Methods: Thirteen low-risk prostate (without lymph-nodes irradiation) and 13 high-risk prostate (with lymph-nodes irradiation) treatments were retrospectively taken from our clinical database and re-optimized using two different automated engines implemented in the Pinnacle treatment system. These two automated engines, the currently used Autoplanning and the new Personalized are both template-based algorithms that use a wish-list to formulate the planning goals and an iterative approach able to mimic the planning procedure usually adopted by experienced planners. In addition, the new Personalized module integrates a new engine, the Feasibility module, able to generate an “a priori” DVH prediction of the achievability of planning goals. Comparison between clinically accepted manually generated (MP) and automated plans generated with both Autoplanning (AP) and Personalized engines (Pers) were performed using dose-volume histogram metrics and conformity indexes. Three different normal tissue complication probabilities (NTCPs) models were used for rectal toxicity evaluation. The planning efficiency and the accuracy of dose delivery were assessed for all plans. Results: For similar targets coverage, Pers plans reported a significant increase of dose conformity and less irradiation of healthy tissue, with significant dose reduction for rectum, bladder, and femurs. On average, Pers plans decreased rectal mean dose by 11.3 and 8.3 Gy for low-risk and high-risk cohorts, respectively. Similarly, the Pers plans decreased the bladder mean doses by 7.3 and 7.6 Gy for low-risk and high-risk cohorts, respectively. The integral dose was reduced by 11–16% with respect to MP plans. Overall planning times were dramatically reduced to about 7 and 15 min for Pers plans. Despite the increased complexity, all plans passed the 3%/2 mm γ-analysis for dose verification. Conclusions: The Personalized engine provided an overall increase of plan quality, in terms of dose conformity and sparing of normal tissues for prostate cancer patients. The Feasibility “a priori” DVH prediction module provided OARs dose sparing well beyond the clinical objectives. The new Pinnacle Personalized algorithms outperformed the currently used Autoplanning ones as solution for treatment planning automation

The contest between internal and external-beam dosimetry: The Zeno's paradox of Achilles and the tortoise.

Radionuclide therapy, also called molecular radiotherapy (MRT), has come of age, with several novel radiopharmaceuticals being approved for clinical use or under development in the last decade. External beam radiotherapy (EBRT) is a well-established treatment modality, with about half of all oncologic patients expected to receive at least one external radiation treatment over their disease course. The efficacy and the toxicity of both types of treatment rely on the interaction of radiation with biological tissues. Dosimetry played a fundamental role in the scientific and technological evolution of EBRT, and absorbed doses to the target and to the organs at risk are calculated on a routine basis. In contrast, in MRT the usefulness of internal dosimetry has long been questioned, and a structured path to include absorbed dose calculation is missing. However, following a similar route of development as EBRT, MRT treatments could probably be optimized in a significant proportion of patients, likely based on dosimetry and radiobiology. In the present paper we describe the differences and the similarities between internal and external-beam dosimetry in the context of radiation treatments, and we retrace the main stages of their development over the last decades

Dynamic11 c-methionine pet-ct: Prognostic factors for disease progression and survival in patients with suspected glioma recurrence

Purpose: The prognostic evaluation of glioma recurrence patients is important in the therapeutic management. We investigated the prognostic value of11 C-methionine PET-CT (MET-PET) dynamic and semiquantitative parameters in patients with suspected glioma recurrence. Methods: Sixty-seven consecutive patients who underwent MET-PET for suspected glioma recurrence at MR were retrospectively included. Twenty-one patients underwent static MET-PET; 46/67 underwent dynamic MET-PET. In all patients, SUVmax, SUVmean and tumour-to-background ratio (T/B) were calculated. From dynamic acquisition, the shape and slope of time-activity curves, time-to-peak and its SUVmax (SUVmaxTTP ) were extrapolated. The prognostic value of PET parameters on progression-free (PFS) and overall survival (OS) was evaluated using Kaplan–Meier survival estimates and Cox regression. Results: The overall median follow-up was 19 months from MET-PET. Recurrence patients (38/67) had higher SUVmax (p = 0.001), SUVmean (p = 0.002) and T/B (p < 0.001); deceased patients (16/67) showed higher SUVmax (p = 0.03), SUVmean (p = 0.03) and T/B (p = 0.006). All static parameters were associated with PFS (all p < 0.001); T/B was associated with OS (p = 0.031). Regarding kinetic analyses, recurrence (27/46) and deceased (14/46) patients had higher SUVmaxTTP (p = 0.02, p = 0.01, respectively). SUVmaxTTP was the only dynamic parameter associated with PFS (p = 0.02) and OS (p = 0.006). At univariate analysis, SUVmax, SUVmean, T/B and SUVmaxTTP were predictive for PFS (all p < 0.05); SUVmaxTTP was predictive for OS (p = 0.02). At multivariate analysis, SUVmaxTTP remained significant for PFS (p = 0.03). Conclusion: Semiquantitative parameters and SUVmaxTTP were associated with clinical outcomes in patients with suspected glioma recurrence. Dynamic PET-CT acquisition, with static and kinetic parameters, can be a valuable non-invasive prognostic marker, identifying patients with worse prognosis who require personalised therapy

Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer

Purpose: To test a short 2-[18F]Fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET dynamic acquisition protocol to calculate Ki using regional Patlak graphical analysis in patients with non-small-cell lung cancer (NSCLC). Methods: 24 patients with NSCLC who underwent standard dynamic 2-[18F]FDG acquisitions (60 min) were randomly divided into two groups. In group 1 (n = 10), a population-based image-derived input function (pIDIF) was built using a monoexponential trend (10–60 min), and a leave-one-out cross-validation (LOOCV) method was performed to validate the pIDIF model. In group 2 (n = 14), Ki was obtained by standard regional Patlak plot analysis using IDIF (0–60 min) and tissue response (10–60 min) curves from the volume of interests (VOIs) placed on descending thoracic aorta and tumor tissue, respectively. Moreover, with our method, the Patlak analysis was performed to obtain Ki,s using IDIFFitted curve obtained from PET counts (0–10 min) followed by monoexponential coefficients of pIDIF (10–60 min) and tissue response curve obtained from PET counts at 10 min and between 40 and 60 min, simulating two short dynamic acquisitions. Both IDIF and IDIFFitted curves were modeled to assume the value of 2-[18F]FDG plasma activity measured in the venous blood sampling performed at 45 min in each patient. Spearman's rank correlation, coefficient of determination, and Passing–Bablok regression were used for the comparison between Ki and Ki,s. Finally, Ki,s was obtained with our method in a separate group of patients (group 3, n = 8) that perform two short dynamic acquisitions. Results: Population-based image-derived input function (10–60 min) was modeled with a monoexponential curve with the following fitted parameters obtained in group 1: a = 9.684, b = 16.410, and c = 0.068 min−1. The LOOCV error was 0.4%. In patients of group 2, the mean values of Ki and Ki,s were 0.0442 ± 0.0302 and 0.33 ± 0.0298, respectively (R2 = 0.9970). The Passing–Bablok regression for comparison between Ki and Ki,s showed a slope of 0.992 (95% CI: 0.94–1.06) and intercept value of −0.0003 (95% CI: −0.0033–0.0011). Conclusions: Despite several practical limitations, like the need to position the patient twice and to perform two CT scans, our method contemplates two short 2-[18F]FDG dynamic acquisitions, a population-based input function model, and a late venous blood sample to obtain robust and personalized input function and tissue response curves and to provide reliable regional Ki estimation

Automated detection and classification of tumor histotypes on dynamic PET imaging data through machine-learning driven voxel classification

2-deoxy-2-fluorine-(18F)fluoro-D-glucose Positron Emission Tomography/Computed Tomography (18F-FDG-PET/CT) is widely used in oncology mainly for diagnosis and staging of various cancer types, including lung cancer, which is the most common cancer worldwide. Since histopathologic subtypes of lung cancer show different degree of 18F-FDG uptake, to date there are some diagnostic limits and uncertainties, hindering an 18F-FDG-PET-driven classification of histologic subtypes of lung cancers. On the other hand, since activated macrophages, neutrophils, fibroblasts and granulation tissues also show an increased 18F-FDG activity, infectious and/or inflammatory processes and post-surgical and post-radiation changes may cause false-positive results, especially for lymph-nodes assessment. Here we propose a model-free, machine-learning based algorithm for the automated classification of adenocarcinoma, the most common type of lung cancer, and other types of tumors. Input for the algorithm are dynamic acquisitions of PET data (dPET), providing for a spatially and temporally resolved characterization of the uptake kinetic. The algorithm consists in a trained Random Forest classifier which, relying contextually on several spatial and temporal features of 18F-FDG uptake, generates as an outcome probability maps allowing to distinguish adenocarcinoma from other lung histotype and to identify metastatic lymph-nodes, ultimately increasing the specificity of the technique. Its performance, evaluated on a dPET dataset of 19 patients affected by primary lung cancer, provides a probability 0.943 ± 0.090 for the detection of adenocarcinoma. The use of this algorithm will guarantee an automatic and more accurate localization and discrimination of tumors, also providing a powerful tool for detecting at which extent tumor has spread beyond a primary tumor into lymphatic system